Once it is recognized that a virtual image (VM) is behaving poorly, through the use of a range of current art techniques, and it is determined that a fallback to a prior version is needed, there are no clear means to determine which prior image should be used. Simply rolling back to the most recent prior version may not resolve the issue, consequently the customer may have to iteratively revert to other prior versions until a good, stable image is found. There is currently no clear method to determine to which prior release to revert to beyond “random choice”. Current systems typically revert to the immediate prior version of the VM, doing so without any level of evaluation of what was driving the undesirable behavior in the current version. Change management systems exist today to indicate when and why a change was made but these systems are consulted by humans instead of providing an automated rationale for determining the rollback version. Thus, these prior art approaches are prone to human error, and require human-driven analysis time to determine an appropriate image.